Find the artificial intelligence based software for radiology that you are looking for. All products listed are available for the European market (CE marked).
Find the artificial intelligence based software for radiology that you are looking for. All products listed are available for the European market (CE marked).
31 of 309 products
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And distribution, Classification, Fibrotic area localization, Lung and lobe segmentation, Pneumonia score
Lung Texture defines the fibrotic area of the lungs in 6 patterns and automatically generates a report by analyzing the location and distribution. Quantitative analysis help with difficult reading cases and reduce deviations from different reading techniques for diagnosis.
Fracture detection
RBfracture is an automated tool to diagnose fractures on x-ray.
Bonescreen
Subspeciality: MSK
Modality: CT
Source: Vendor
Bone mineral density measurement, Risk score , Vertebral fracture detection
SpineQ is software device analyzes bone density and detects vertebral fractures on CT-scans.
Computer-aided diagnosis tool, Intended to help radiologists and emergency physicians to detect and localize abnormalities on standard x-rays
AZmeasure delivers automated characterization of osteo-articular geometries, including lengths and angular positions of hip, knee and foot. It focuses on MSK (musculoskeletal) radiography.
Computer-aided diagnosis tool, Intended to help radiologists and emergency physicians to detect and localize abnormalities on standard x-rays
AZchest is intended for use in the analysis of chest X-rays. It is designed to assist healthcare professionals by automatically detecting, categorizing, and reporting on cardiac and pulmonary abnormalities.
Area quantification, Disease recognition, Distance quantification, Doppler modality quantification, Volume quantification
Ligence has developed a platform for automated analysis and reporting of 2D transthoracic echocardiography studies. The Ligence Heart platform reads DICOM format data, recognises image views, heart cycle, performs measurements and generates a report based on findings. It allows medical practitioners to skip manual measurements during the examination.
And ejection fraction, Heart ventricles segmentation, Myocardial mass, Quantification of ventricular volumes, Wall motion classification
The AI4CMR software performs a automatic cardiac segmentation and interpretation of Cardiac Magnetic Resonance (CMR), allowing quantification of various parameters without the need for intervention by a medical professional.
It automatically identifies cases with normal left and right ventricle wall motion (regional contractility), aimed at increasing awareness for the cases with suspicious wall motion abnormalities to the reporting physicians.
Editable report, Editable separate pathology report, Lumbar spine annotation, Measurement calculation based on segmentation, Smart navigation
CoLumbo is an AI assistant software for the interpretation of lumbar spine MR scans. It is a deep learning algorithm that aims to help radiologists reduce the patient examination reading and reporting time, and increase the accuracy of measurements, and facilitate standardization in spine MRI reporting and increase the patient – physician communication and trust.
Confidence bar, Detection of up to 130 findings (acute and chronic) on brain CT, Normal/abnormal differentiation, Notification, Visualisation, Worklist triage
Harrison.ai CT Brain is an AI clinical decision-support solution for non-contrast head CT, detecting up to 130 findings. Features include: • customisable, interactive viewer that integrates into PACS/RIS • a confidence bar displaying the likelihood of the finding and uncertainty of the AI model • worklist triage.
Confidence bar, Detection of up to 124 chest findings + detection of suspected tuberculosis, Normal/abnormal differentiation, Notification, Worklist triage
Harrison.ai Chest X-Ray is an AI clinical decision-support solution for chest X-ray, assisting clinicians to interpret chest X-Rays studies by detecting up to 124 findings + suspected tuberculosis. It acts as a second pair of eyes providing notification of suspected findings. Features include: • analysing up to three images per study including frontal and lateral images • a confidence bar displaying the likelihood of the finding and uncertainty of the AI model • customisable user interface that integrates seamlessly into PACS and RIS. • worklist triage
AI- supported prostate segmentation and volume, Lesion segmentation, PI-RADS v2.1 scoring support, Structured report, Volumes and risk scores
Prostate Intelligence software intended to assist analysis of MRI for suspected prostate cancer. It uses a combination of image processing, deep learning and machine learning methods, to segment the prostate, identify regions of interest, and calculate risk scores.